Remove cuDF dependency from pylibcudf column from_device tests (#16441)

This removes the need to `import cudf` in `test_column_from_device` and removes a runtime dependency on numpy in the associated pylibcudf column method.

Authors:
  - https://github.com/brandon-b-miller
  - Thomas Li (https://github.com/lithomas1)

Approvers:
  - Thomas Li (https://github.com/lithomas1)
  - Lawrence Mitchell (https://github.com/wence-)

URL: #16441

python/cudf/cudf/_lib/pylibcudf/column.pyx

@@ -15,13 +15,11 @@ from cudf._lib.pylibcudf.libcudf.types cimport size_type
 
 from .gpumemoryview cimport gpumemoryview
 from .scalar cimport Scalar
-from .types cimport DataType, type_id
+from .types cimport DataType, size_of, type_id
 from .utils cimport int_to_bitmask_ptr, int_to_void_ptr
 
 import functools
 
-import numpy as np
-
 
 cdef class Column:
     """A container of nullable device data as a column of elements.
@@ -303,14 +301,15 @@ cdef class Column:
             raise ValueError("mask not yet supported.")
 
         typestr = iface['typestr'][1:]
+        data_type = _datatype_from_dtype_desc(typestr)
+
         if not is_c_contiguous(
             iface['shape'],
             iface['strides'],
-            np.dtype(typestr).itemsize
+            size_of(data_type)
         ):
             raise ValueError("Data must be C-contiguous")
 
-        data_type = _datatype_from_dtype_desc(typestr)
         size = iface['shape'][0]
         return Column(
             data_type,

python/cudf/cudf/_lib/pylibcudf/libcudf/types.pxd

@@ -98,3 +98,5 @@ cdef extern from "cudf/types.hpp" namespace "cudf" nogil:
         HIGHER
         MIDPOINT
         NEAREST
+
+    cdef size_type size_of(data_type t) except +

python/cudf/cudf/_lib/pylibcudf/types.pxd

@@ -27,3 +27,5 @@ cdef class DataType:
 
     @staticmethod
     cdef DataType from_libcudf(data_type dt)
+
+cpdef size_type size_of(DataType t)

python/cudf/cudf/_lib/pylibcudf/types.pyx

@@ -2,7 +2,12 @@
 
 from libc.stdint cimport int32_t
 
-from cudf._lib.pylibcudf.libcudf.types cimport data_type, size_type, type_id
+from cudf._lib.pylibcudf.libcudf.types cimport (
+    data_type,
+    size_of as cpp_size_of,
+    size_type,
+    type_id,
+)
 from cudf._lib.pylibcudf.libcudf.utilities.type_dispatcher cimport type_to_id
 
 from cudf._lib.pylibcudf.libcudf.types import type_id as TypeId  # no-cython-lint, isort:skip
@@ -69,6 +74,15 @@ cdef class DataType:
         ret.c_obj = dt
         return ret
 
+cpdef size_type size_of(DataType t):
+    """Returns the size in bytes of elements of the specified data_type.
+
+    Only fixed-width types are supported.
+
+    For details, see :cpp:func:`size_of`.
+    """
+    with nogil:
+        return cpp_size_of(t.c_obj)
 
 SIZE_TYPE = DataType(type_to_id[size_type]())
 SIZE_TYPE_ID = SIZE_TYPE.id()

python/cudf/cudf/pylibcudf_tests/test_column_from_device.py

@@ -4,7 +4,8 @@
 import pytest
 from utils import assert_column_eq
 
-import cudf
+import rmm
+
 from cudf._lib import pylibcudf as plc
 
 VALID_TYPES = [
@@ -35,17 +36,39 @@ def valid_type(request):
     return request.param
 
 
+class DataBuffer:
+    def __init__(self, obj, dtype):
+        self.obj = rmm.DeviceBuffer.to_device(obj)
+        self.dtype = dtype
+        self.shape = (int(len(self.obj) / self.dtype.itemsize),)
+        self.strides = (self.dtype.itemsize,)
+        self.typestr = self.dtype.str
+
+    @property
+    def __cuda_array_interface__(self):
+        return {
+            "data": self.obj.__cuda_array_interface__["data"],
+            "shape": self.shape,
+            "strides": self.strides,
+            "typestr": self.typestr,
+            "version": 0,
+        }
+
+
 @pytest.fixture
-def valid_column(valid_type):
+def input_column(valid_type):
     if valid_type == pa.bool_():
         return pa.array([True, False, True], type=valid_type)
     return pa.array([1, 2, 3], type=valid_type)
 
 
-def test_from_cuda_array_interface(valid_column):
-    col = plc.column.Column.from_cuda_array_interface_obj(
-        cudf.Series(valid_column)
-    )
-    expect = valid_column
+@pytest.fixture
+def iface_obj(input_column):
+    data = input_column.to_numpy(zero_copy_only=False)
+    return DataBuffer(data.view("uint8"), data.dtype)
+
+
+def test_from_cuda_array_interface(input_column, iface_obj):
+    col = plc.column.Column.from_cuda_array_interface_obj(iface_obj)
 
-    assert_column_eq(expect, col)
+    assert_column_eq(input_column, col)